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dc.contributor.authorHarvey, MRen_US
dc.contributor.authorRodrigues, Jen_US
dc.contributor.authorLane, JCEen_US
dc.contributor.authorWade, RGen_US
dc.contributor.authorBroekstra, DCen_US
dc.contributor.authorHarrison, Cen_US
dc.date.accessioned2023-10-17T14:22:08Z
dc.date.available2023-10-17T14:22:08Z
dc.date.issued2023-09-25en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/91374
dc.description.abstractIn this second of a two-part article, we describe some of the common statistical pitfalls encountered in hand surgery research. These include dichotomania, the 'Table 2 fallacy', p-hacking, regression to the mean, overfitting and unaccounted data clustering. We explain the impact of these pitfalls on hand surgery research and describe techniques to avoid them. The aim of this two-part article was to provide a starting point for hand surgeons to refer to when conducting or analysing research and provide resources and references for interested readers to explore.en_US
dc.format.extent17531934231200354 - ?en_US
dc.languageengen_US
dc.relation.ispartofJ Hand Surg Eur Volen_US
dc.subjectStatisticsen_US
dc.subjectclinical statisticsen_US
dc.subjecthand surgeryen_US
dc.titleStatistics for the hand surgeon. Part 2: avoiding common pitfalls.en_US
dc.typeArticle
dc.identifier.doi10.1177/17531934231200354en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/37747691en_US
pubs.notesNot knownen_US
pubs.publication-statusPublished onlineen_US


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